Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome
Susie Y. Huang,
Thomas Witzel,
Boris Keil,
Alina Scholz,
Mathias Davids,
Peter Dietz,
Elmar Rummert,
Rebecca Ramb,
John E. Kirsch,
Anastasia Yendiki,
Qiuyun Fan,
Qiyuan Tian,
Gabriel Ramos-Llordén,
Hong-Hsi Lee,
Aapo Nummenmaa,
Berkin Bilgic,
Kawin Setsompop,
Fuyixue Wang,
Alexandru V. Avram,
Michal Komlosh,
Dan Benjamini,
Kulam Najmudeen Magdoom,
Sudhir Pathak,
Walter Schneider,
Dmitry S. Novikov,
Els Fieremans,
Slimane Tounekti,
Choukri Mekkaoui,
Jean Augustinack,
Daniel Berger,
Alexander Shapson-Coe,
Jeff Lichtman,
Peter J. Basser,
Lawrence L. Wald,
Bruce R. Rosen
Affiliations
Susie Y. Huang
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Corresponding author.
Thomas Witzel
Q bio Inc., San Carlos, CA, USA
Boris Keil
Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
Alina Scholz
Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
Mathias Davids
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Peter Dietz
Siemens Healthineers, Erlangen, Germany
Elmar Rummert
Siemens Healthineers, Erlangen, Germany
Rebecca Ramb
Siemens Healthineers, Erlangen, Germany
John E. Kirsch
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Anastasia Yendiki
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Qiuyun Fan
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Qiyuan Tian
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Gabriel Ramos-Llordén
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Hong-Hsi Lee
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Aapo Nummenmaa
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Berkin Bilgic
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Kawin Setsompop
Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, USA
Fuyixue Wang
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Alexandru V. Avram
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
Michal Komlosh
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
Dan Benjamini
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
Kulam Najmudeen Magdoom
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
Sudhir Pathak
Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
Walter Schneider
Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
Dmitry S. Novikov
Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
Els Fieremans
Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
Slimane Tounekti
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Choukri Mekkaoui
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Jean Augustinack
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Daniel Berger
Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
Alexander Shapson-Coe
Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
Jeff Lichtman
Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
Peter J. Basser
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
Lawrence L. Wald
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Bruce R. Rosen
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain – from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.
